Edo Bander
... hypotheses and are one of the most practical approaches to certain type of learning problems. Bayesian classifier is competitive with other learning algorithms in many cases and in some situations, it outperforms other methods. The reason why Bayesian algorithm is important to machine learning is be ...
... hypotheses and are one of the most practical approaches to certain type of learning problems. Bayesian classifier is competitive with other learning algorithms in many cases and in some situations, it outperforms other methods. The reason why Bayesian algorithm is important to machine learning is be ...
Resolution Based Explanations for Reasoning in the Description Logic
... it would avoid the exponential blow up of the size of the clauses. Consider the axiom , where E and F are complex concept descriptions. If n is the number of clauses generated by E and m is the number of clauses generated by F then the above formula generates n×m clauses. The reason for the exponent ...
... it would avoid the exponential blow up of the size of the clauses. Consider the axiom , where E and F are complex concept descriptions. If n is the number of clauses generated by E and m is the number of clauses generated by F then the above formula generates n×m clauses. The reason for the exponent ...
Multilinear Representations for Ordinal Utility
... Thus, although u(x, y, z) is not additive, there is a way to structure the assessment process so that complicated interactions are avoided. Ting (1971) gives a highly readable account of the literature on this subject. Nahas (1977) relates and adapts this work to cardinal utility functions. Some ver ...
... Thus, although u(x, y, z) is not additive, there is a way to structure the assessment process so that complicated interactions are avoided. Ting (1971) gives a highly readable account of the literature on this subject. Nahas (1977) relates and adapts this work to cardinal utility functions. Some ver ...
Chapter8
... • Discretization can be useful even if a learning algorithm can be run on numeric attributes directly • Avoids normality assumption in Naïve Bayes and clustering • Examples of discretization we have already encountered: • 1R: uses simple discretization scheme • C4.5 performs local discretization ...
... • Discretization can be useful even if a learning algorithm can be run on numeric attributes directly • Avoids normality assumption in Naïve Bayes and clustering • Examples of discretization we have already encountered: • 1R: uses simple discretization scheme • C4.5 performs local discretization ...
Correlation-based Attribute Selection using Genetic Algorithm
... their fitness: Fitness of the individual chromosome is computed on the basis of its correlation coefficients with other attributes in the population. To find out the correlation between the attributes some normalization is done as shown in the table 3.2.1. ...
... their fitness: Fitness of the individual chromosome is computed on the basis of its correlation coefficients with other attributes in the population. To find out the correlation between the attributes some normalization is done as shown in the table 3.2.1. ...
“Genetic Algorithm as an Attribute Subset Selection tool during
... their fitness: Fitness of the individual chromosome is computed on the basis of its correlation coefficients with other attributes in the population. To find out the correlation between the attributes some normalization is done as shown in the table 3.2.1. ...
... their fitness: Fitness of the individual chromosome is computed on the basis of its correlation coefficients with other attributes in the population. To find out the correlation between the attributes some normalization is done as shown in the table 3.2.1. ...
Ordering attributes for missing values prediction and
... classifier and preprocessor having an attribute order searcher to improve the results. One of the aspects that have influence on the K2 performance is the initial order of the attributes in the data set, however, in most cases, this algorithm is applied without giving special attention to this preor ...
... classifier and preprocessor having an attribute order searcher to improve the results. One of the aspects that have influence on the K2 performance is the initial order of the attributes in the data set, however, in most cases, this algorithm is applied without giving special attention to this preor ...
Word Sense Disambiguation for Arabic Text Categorization
... resource (WN) into text representation, using the ChiSquare, which consists of extracting the k better features best characterizing the category, compared to others representations. The main difficulty in this approach is that it is not capable of determining the correct senses. For a word that has ...
... resource (WN) into text representation, using the ChiSquare, which consists of extracting the k better features best characterizing the category, compared to others representations. The main difficulty in this approach is that it is not capable of determining the correct senses. For a word that has ...
extending office systems to manage administrative knowledge
... Seminal work in knowledge representation was carried out in the ‘70’s and ‘80’s. Current literature in this area, especially as it pertains to CK is sparse for reasons already mentioned. There seem to be two approaches to knowledge engineering which can be thought of as “top-down” and “ bottom up.” ...
... Seminal work in knowledge representation was carried out in the ‘70’s and ‘80’s. Current literature in this area, especially as it pertains to CK is sparse for reasons already mentioned. There seem to be two approaches to knowledge engineering which can be thought of as “top-down” and “ bottom up.” ...
Relational Object Maps for Mobile Robots
... set of entities for each class and the values of all attributes for each entity. In our case, I is an RO-Map consisting of line segments extracted from laser range-scans. A relational clique template C ∈ C is similar to a query in a relational database. It selects tuples from an instantiation I; the ...
... set of entities for each class and the values of all attributes for each entity. In our case, I is an RO-Map consisting of line segments extracted from laser range-scans. A relational clique template C ∈ C is similar to a query in a relational database. It selects tuples from an instantiation I; the ...
Induction of decision trees
... 2. determining the game-theoretic value o f a chess position, with the classes won for white, lost for white, and drawn; and 3. deciding from atmospheric observations whether a severe thunderstorm is unlikely, possible or probable. It might appear that classification tasks are only a minuscule subse ...
... 2. determining the game-theoretic value o f a chess position, with the classes won for white, lost for white, and drawn; and 3. deciding from atmospheric observations whether a severe thunderstorm is unlikely, possible or probable. It might appear that classification tasks are only a minuscule subse ...
filters of lattices with respect to a congruence - DML-PL
... to a congruence θ and there are studied some of their properties. The θ-filters are also characterized in terms of congruence classes. Equivalent conditions are derived for every filter of a lattice to become a θ-filter. Finally, an isomorphism is obtained between the lattice of θ-filters of a latti ...
... to a congruence θ and there are studied some of their properties. The θ-filters are also characterized in terms of congruence classes. Equivalent conditions are derived for every filter of a lattice to become a θ-filter. Finally, an isomorphism is obtained between the lattice of θ-filters of a latti ...
Mining Incomplete Data with Many Missing Attribute Values
... idea of rough set theory [1], [2]. For incomplete data sets there exist many definitions of approximations. In this paper, we use three types of approximations: singleton, subset and concept [3]. A probabilistic (or parameterized) approximation, associated with a probability (parameter) α, is a gene ...
... idea of rough set theory [1], [2]. For incomplete data sets there exist many definitions of approximations. In this paper, we use three types of approximations: singleton, subset and concept [3]. A probabilistic (or parameterized) approximation, associated with a probability (parameter) α, is a gene ...
Bicartesian closed categories and logic
... These data are moreover required to satisfy the following laws: • For all f in C ( A, B), f ◦ id A = f = idB ◦ f • If f ∈ C ( A, B), g ∈ C ( B, C ), and h ∈ C (C, D ), then h ◦ ( g ◦ f ) = (h ◦ g) ◦ f When the category C is clear from context, we may write f : A → B to mean that f ∈ C ( A, B). Examp ...
... These data are moreover required to satisfy the following laws: • For all f in C ( A, B), f ◦ id A = f = idB ◦ f • If f ∈ C ( A, B), g ∈ C ( B, C ), and h ∈ C (C, D ), then h ◦ ( g ◦ f ) = (h ◦ g) ◦ f When the category C is clear from context, we may write f : A → B to mean that f ∈ C ( A, B). Examp ...
Thesauri and Formal Concept Analysis
... in 517.2. He also noted, however, that the hierarchical structure did not always show relationships that could be shown, given the information in the Thesaurus (Figure 4). Warfel then went on to develop an algorithm which assumed an equivalence table of such related categories. This algorithm could, ...
... in 517.2. He also noted, however, that the hierarchical structure did not always show relationships that could be shown, given the information in the Thesaurus (Figure 4). Warfel then went on to develop an algorithm which assumed an equivalence table of such related categories. This algorithm could, ...
Presentation
... Incoming signals, {x,w} are associated with model-concepts (m) – creating phenomena (of the MFT-mind), which are understood as objects, situations, phrases,… – in other words signal subsets acquire meaning (e.g., a subset of retinal signals acquires a meaning of a chair) ...
... Incoming signals, {x,w} are associated with model-concepts (m) – creating phenomena (of the MFT-mind), which are understood as objects, situations, phrases,… – in other words signal subsets acquire meaning (e.g., a subset of retinal signals acquires a meaning of a chair) ...
A Formal Characterization of Concept Learning in Description Logics
... Definition 3 (Refinement chain in DLs). Given a downward (resp., upward) refinement operator ρ (resp., δ) for a quasi-ordered search space (DLH , v), a refinement chain from C ∈ DLH to D ∈ DLH is a sequence C = C0 , C1 , . . . , Cn = D such that Ci ∈ ρ(Ci−1 ) (resp., Ci ∈ δ(Ci−1 )) for every 1 ≤ i ...
... Definition 3 (Refinement chain in DLs). Given a downward (resp., upward) refinement operator ρ (resp., δ) for a quasi-ordered search space (DLH , v), a refinement chain from C ∈ DLH to D ∈ DLH is a sequence C = C0 , C1 , . . . , Cn = D such that Ci ∈ ρ(Ci−1 ) (resp., Ci ∈ δ(Ci−1 )) for every 1 ≤ i ...
The Even More Irresistible SROIQ
... We describe an extension, called SROIQ, of the description logic (DL) SHOIN (14) underlying OWL-DL (9).1 SHOIN can be said to provide most expressive means that one could reasonably expect from the logical basis of an ontology language, and to constitute a good compromise between expressive power an ...
... We describe an extension, called SROIQ, of the description logic (DL) SHOIN (14) underlying OWL-DL (9).1 SHOIN can be said to provide most expressive means that one could reasonably expect from the logical basis of an ontology language, and to constitute a good compromise between expressive power an ...
Correlation-Based Refinement of Rules with Numerical Attributes Andr´e Melo Martin Theobald Johanna V¨olker
... conf (h:-b) = supp({h, b})/supp(b). Its support is given by the number n+ of covered positive examples, i.e., supp(h:b) = n+ ({h, b}). We consider a base rule interesting if it has a refined rule that satisfies the minimum support, confidence and confidence gain thresholds. As we want to efficiently ...
... conf (h:-b) = supp({h, b})/supp(b). Its support is given by the number n+ of covered positive examples, i.e., supp(h:b) = n+ ({h, b}). We consider a base rule interesting if it has a refined rule that satisfies the minimum support, confidence and confidence gain thresholds. As we want to efficiently ...
Learning Concepts by Interaction
... series into another by stretching and compressing the horizontal (temporal) axis of one series relative to the other [14]. If two multivariate series are very similar, relatively little stretching and compressing is required to warp one series into the other. A number that indicates the remaining mi ...
... series into another by stretching and compressing the horizontal (temporal) axis of one series relative to the other [14]. If two multivariate series are very similar, relatively little stretching and compressing is required to warp one series into the other. A number that indicates the remaining mi ...
SOFTWARE ARCHITECTURE FOR BUILDING INTELLIGENT USER
... learners. All performed actions are important in the way that they will provide important information regarding the behavior of the learners. This will represent in a hard and the structured form the experience of the crowd. The core idea of the paper is represented by a custom representation of thi ...
... learners. All performed actions are important in the way that they will provide important information regarding the behavior of the learners. This will represent in a hard and the structured form the experience of the crowd. The core idea of the paper is represented by a custom representation of thi ...
Characterization - NYU Computer Science
... J. Gray, S. Chaudhuri, A. Bosworth, A. Layman, D. Reichart, M. Venkatrao, F. Pellow, and H. Pirahesh. Data cube: A relational aggregation operator generalizing group-by, cross-tab and sub-totals. Data Mining and Knowledge Discovery, 1:29-54, 1997. J. Han, Y. Cai, and N. Cercone. Data-driven disc ...
... J. Gray, S. Chaudhuri, A. Bosworth, A. Layman, D. Reichart, M. Venkatrao, F. Pellow, and H. Pirahesh. Data cube: A relational aggregation operator generalizing group-by, cross-tab and sub-totals. Data Mining and Knowledge Discovery, 1:29-54, 1997. J. Han, Y. Cai, and N. Cercone. Data-driven disc ...
Oriented k-windows: A PCA driven clustering method
... hyperrectangles together with merging is effective in discovering clusters. All movements, however, were constrained to be parallel to any one of the standard cartesian axes. We next consider the possibility of allowing the hyperrectangles adapt both their orientation and size, as means to more effe ...
... hyperrectangles together with merging is effective in discovering clusters. All movements, however, were constrained to be parallel to any one of the standard cartesian axes. We next consider the possibility of allowing the hyperrectangles adapt both their orientation and size, as means to more effe ...